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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

The structure of high-Mg alkali-bearing aluminosilicate glasses investigated in situ at ambient and high pressure by multi-angle energy dispersive X-ray diffraction and infrared microspectroscopy

The structural properties of synthetic high-Mg alkali-bearing aluminosilicate glasses analogues of natural picritic-to-komatiitic magmas were investigated in situ by multiangle energy dispersive X-ray diffraction at 2.1 GPa and ambient pressure and by Fourier Transform infrared spectroscopy up to 5.4 GPa in a cycle of compression and decompression experiments. Our results show that the intermediate range ordering of the glass structure at 2.1 GPa is 3.14 Å, increasing to 3.19 Å when decompressed. The local structure shows T-O lengths of 1.66 Å (2.1 GPa) and 1.65 Å (ambient pressure), T-T distances of 3.19 Å at high pressure, which lengthen to 3.21 Å at ambient pressure, causing the T-O-T angle of 147° determined at 2.1 GPa to widen to 154° upon decompression. The deconvoluted infrared spectra result in the presence of Q 1 , Q 2 , Q 3 populations in the aluminosilicate spectral region, whose proportions remain relatively unchanged up to 5.4 GPa. The structural response of the investigated glasses to cold-compression does not involve changes in polymerization, but rather a shrinking and compaction of the structure as evidenced by the Qn species shifting to higher wavenumbers as a function of pressure. The structural properties determined from X-ray diffraction for this glass composition are discussed together with those of glasses emerging from previous studies to highlight a compositional dependence mainly dictated by the amount of SiO 2 and Al 2 O 3 .

glass structure↗
DOE OSTI2025

Use of Fisher's Ratio assisted multivariate curve resolution- alternating least squares for discovery-based analysis using ultrahigh pressure liquid chromatography-high resolution mass spectrometry

Non-targeted analysis of complex chemical mixtures can be difficult considering the convoluted nature of the matrix and the potential unknown chemical differences between samples or classes of samples. Ultrahigh pressure liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UHPLC-QTOF) is an ideal technique to probe chemical differences for a wide variety of samples. While UHPLC-QTOF can discover minute chemical differences down to low part per billion (ppb) concentrations with a high degree of confidence, the application of high-resolution mass spectrometry can yield massive amounts of information (∼ 10 gb per sample) that cannot be analyzed manually. Therefore, the application of chemometric techniques is mandatory for the interrogation of complex samples. Fisher's ratio (FR) assisted multivariate curve resolution-alternating least squares (MCR-ALS) was used to the discover and identify the chemical differences between two classes of materials: 1) a pond water matrix and 2) the matrix spiked with a pharmaceutical standard mix containing 17 compounds. Thirteen of the seventeen spiked compounds were discovered using FR analysis, and then five were successfully deconvoluted using MCR-ALS wherein the number of curves chosen were automatically determined using singular value decomposition (SVD). In conclusion, the use of an automated FR assisted MCR-ALS will aid in discovering trace levels of chemical components without the need for the researcher to provide potentially biased input which will aid in non-targeted workflow.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Exploring the impact of nucleotide length on lipid nanoparticle structure and properties

Lipid nanoparticles (LNPs) are versatile carriers for nucleic acid (NA) therapeutics, including ASOs, siRNA, mRNA, and poly-IC. While lipid composition is known to influence LNP properties, the impact of NA length on morphology and internal structure is less understood, particularly during the stages of carrier–cargo assembly. Here, we examine NA length and lipid composition immediately after mixing using high-throughput SAXS, dynamic light scattering, and cryogenic electron microscopy. All LNPs form ordered NA/lipid compartments, with longer NAs promoting inverse hexagonal (H II ) phases and larger intercompartment distances. In contrast, short NAs, especially in formulations with SM102 ionizable lipid, favor lamellar phases. SAXS peak deconvolution quantifies ordered versus disordered phases via a Robustness of Ordered Phase factor, which correlates with particle size and encapsulation efficiency. Formulations with MC3 ionizable and DOPE helper lipids exhibit the most stable H II -phase packing, highlighting the role of helper-lipid curvature in compartment stabilization. Variations in NA compartmentalization indicate differences in payload capacity, offering a framework for rational LNP design across diverse nucleic acid cargos.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Probing thermodynamics of radiogenic helium and defects in $δ$-plutonium alloys and interactions with adsorbed environmental gases

Differential scanning calorimetry coupled with simultaneous evolved gas analysis (DSC-EGA) on aged δ-Pu samples shows that most radiogenic helium remains trapped within the Pu matrix at temperatures very close to, or slightly above, the melting temperature. Our results indicate that helium release from 50-year-old δ-Pu occurs as a burst just below the melting temperature (>0.994 T m ), with subsequent pressure oscillations as temperature increases. Subordinate quantities of H 2 were also released along with helium. Here, the helium emission tails off and ceases above ~720 – 750°C. In a δ-Pu alloy aged 6 years, the initial helium burst occurs slightly above melting (~1.015 – 1.042 T m ), with a discrete, larger helium spike occurring between 670 and 686°C. The proximity of helium release to the liquidus transition presented challenges in the deconvolution of overlapping process enthalpies, the liquidus endotherm, and the exotherm resulting from bubble collapse, annealing and gas expulsion. Helium’s strong affinity for vacancy binding in a 2He-vac configuration is predicted by Density Functional Theory (DFT) modeling. The measured stored energy associated with the He release events in a 50-year-old δ alloy is on the order of ~ 10–11 J/g, which is significantly higher than stored energies measured in the sub-solidus regimes (~2 J/g) that are related to the solid-state annealing of processing- and radiation-induced defects. This implies that aged δ Pu alloys have a remarkable resilience to accommodate the lattice strain produced by the internal pressure of the helium bubbles and provides further insight into the thermodynamic behavior of aged δ Pu.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Cosolvent-tuned interactions in ionic liquids: A vibrational and quantum-chemical study of ethylene glycol ratio effects

Ionic liquids (ILs) are attractive media for CO 2 capture but remain limited by viscosity and cost. Blending ILs with ethylene glycol (EG) is a practical route to mitigate these constraints, yet the molecular origins of cosolvent effects and their dependence on composition are not well resolved. We combine Fourier-transform infrared (FT-IR) spectroscopy with quantum-chemical (DFT) analysis to elucidate how the IL:EG molar ratio modulates intermolecular interactions and electronic structure. Computed vibrational frequencies enable mode assignment and deconvolution of overlapping bands, revealing systematic, ratio-dependent shifts and broadenings in (i) EG O–H stretching, (ii) cation and EG C–H stretchings (imidazolium C2–H, C4–H, C5–H, methyl and ethyl groups, -CH2 of EG), (iii) anion signature modes (e.g., CN motifs), and (iv) EG C–O and C–C stretchings, consistent with the redistribution of hydrogen-bonding networks. Molecular electrostatic potential (MESP) maps quantify attenuation of extreme potential regions with increasing EG, indicating progressive screening of cation–anion electrostatic interactions. Quantum Theory of Atoms in Molecules (QTAIM) identifies emergent bond critical points between EG and the IL ions, while Reduced Density Gradient–Noncovalent Interaction (RDG–NCI) analysis differentiates strong directional hydrogen bonds from dispersive contacts across compositions. Together, these results show that EG fraction controls a switch from predominantly ion–ion to mixed ion–EG coordination, altering local polarity and polarizability that underlie the observed FT-IR trends. The framework provides composition–structure–spectrum relationships that can guide rational selection of IL:EG ratios to balance favorable molecular interactions with practical performance targets in scalable CO 2 capture systems.

DAC↗
DOE OSTI2025

A critical analysis of U-Pu-Zr phase transitions using calorimetric, microstructural, and phase equilibria data

Metallic fuels consisting primarily of uranium, plutonium, and zirconium (U-Pu-Zr) are a leading material candidate for fast-spectrum nuclear reactors. Early demonstration programs proved the principle of safe and efficient fast reactor operation, however there is still considerable uncertainty regarding the phase equilibria and microstructural evolution across the ternary composition space. Quantitative phase formation and identification measurements are scarce and often incomplete, with studies reporting either phase transition temperatures or phase identification data, but not both from the same specimens. In this study, we critically compared experimental and calculated phase transition data and correlated with the microstructure and phase characterization data of as-cast and annealed U-Pu-Zr alloys. Differential scanning calorimetry (DSC) was used to measure phase transitions in the subsolidus regions (723−948 K) of three ternary U-Pu-Zr alloys with similar plutonium concentrations but various U/Zr ratios. Due to sluggish kinetics and narrow ranges of phase stability, complex peaks required the use of a Frazier-Suzuki peak fitting algorithm to deconvolute and calculate transition peak temperatures and enthalpies. We also identified trends of phase transition behavior by critically comparing our DSC data with previous phase transition measurements as well as historical and calculated phase equilibrium diagrams. In conclusion, this provides a critical approach for benchmarking and assessing the quality of new U-Pu-Zr phase equilibria data prior to its incorporation into nuclear material databases.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Identifying electrochemical processes by distribution of relaxation times in proton exchange membrane electrolyzers

Distribution of relaxation time (DRT) is used to interpret electrochemical impedance spectroscopy (EIS) for proton exchange membrane (PEM) water electrolyzers, with an attempt to separate overlapped relaxation processes in Nyquist plots. By varying operating conditions and catalyst loadings, four main relaxation peaks arising from EIS can be identified and successfully separated from low to high frequencies as (P1) mass transport, (P2) oxygen evolution reaction kinetics, (P3) reaction kinetics (with faster time constant than P2), and (P4) ionic transport. Here, the shape, height, and frequency of the DRT peaks change with different membrane electrode assembly (MEA) configurations. Electron microscopy reveals distinct features from the cross-sectioned MEAs which verify critical DRT results in that increasing the iridium (Ir)-anode loading from 0.2 mgIr/cm 2 to 1.5 mgIr/cm 2 reduces kinetic losses due to higher site-access; a thick and compacted anode, however, also triggers higher ohmic resistances from membrane/catalyst layer hydration and increases transport losses due to longer ionomer pathways. DRT provides higher resolution to EIS for deconvoluting processes with different relaxation times and the quantification of DRT peaks improves the accounting of total losses from each process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Optimizing Porous Transport Layer Porosity for Proton Exchange Membrane Water Electrolysis

An empirical model is presented that describes anode-side losses related to porous transport layer (PTL) morphology in proton exchange membrane water electrolysis (PEMWE). The model is based on an advanced voltage breakdown analysis that links various overpotentials to PTL morphology. Custom Ti PTLs, spanning uncommonly low porosities (22 - 31%), were fabricated and analyzed with X-ray CT to obtain pore and particle size distributions. Particle size distributions were consistent across samples with an average particle diameter of 12.0?..mu..m, whereas average pore diameters ranged from 6.0 to 7.0?..mu..m. The PTLs were tested in standard PEMWE cell assemblies with anode catalyst loadings of 0.1 mgIr cm-2 to obtain polarization curves, electrochemical impedance spectra, and augmented Tafel analysis. The PTL-dependent anode side losses were deconvoluted and assigned to excess utilization, concentration, ion transport resistance, and electrical contact resistance overpotentials. The data and model reveal an optimal 20 - 28% PTL porosity region where utilization and contact resistance overpotentials are minimized without triggering concentration and ion transport losses related to water deprivation. The optimal PTL porosity depends on the operating current density and is demonstrated at realistic PEMWE water flow rates to establish PTL design guidance for operation at scale.

08 HYDROGEN↗
DOE OSTI2024

Characterization of Fuel Cladding Chemical Interaction on a High Burnup U-10Zr Metallic Fuel via Electron Energy Loss Spectroscopy Enhanced by Machine Learning

Fuel cladding chemical interaction (FCCI) is one of the main performance limiting factors for metallic nuclear fuels. The interaction destabilizes the martensitic microstructure and deteriorates mechanical properties of HT-9 cladding. The detection of low atomic number elements (Z<10) and overlapping of elemental peaks can be problematic in interpreting energy dispersive X-ray spectroscopy (EDS) data. Electron energy loss spectroscopy (EELS) provides precise elemental edge energy values and can detect elements with a low atomic number. This work utilizes EELS to study the distribution of lanthanides and light elements at the interaction region. The sample was prepared from the FCCI region of a U-10Zr (wt.%) solid fuel with HT-9 cladding, irradiated to a burnup of 13.2 at.%. Processing the EELS data included three major steps: 1) enhance the signal to noise ratio by denoising the spectrum with principal component analysis (PCA) method, removing background and performing deconvolution; 2) identify chemical elements with core energy loss edges; 3) confirm different phases using a popular machine learning method, K-means. This work presents qualitative assessment of lanthanides and light elements like carbon (C) and oxygen (O) enhanced by the application of machine learning algorithms. By comparing with EDS elemental maps, EELS provides higher resolution chemical maps, reveals the distribution of carbon at the interaction region supporting the formation of zirconium carbide, a rind-like microstructure feature that was proposed to mitigate the chemical interaction. Furthermore, the plasmon peak map was also found to indicate an energy shift associated with the formation of phases/compounds. K-means clustering method was used on the processed electron energy loss (EEL) spectrum to automatically reveal different phases. The resulting clustered maps from K-means clustering align well with elemental maps confirming certain phases, especially Fe-Ce and Zr-C, in the FCCI region.

EELS↗
DOE OSTI2024

Development and demonstration of a BISON–Griffin modeling framework for the design of targeted TRISO transient experiments in the Transient Reactor Test Facility

Uranium oxycarbide (UCO)-bearing tri-structural isotropic (TRISO) particle fuels are expected to be used in numerous U.S. commercial reactor applications within the next decade. Here, in this work, we reviewed historical particle fuel transient experiments to identify gaps in TRISO fuel performance transient testing. A BISON–Griffin modeling framework was then developed to conduct preliminary TRISO transient analyses and begin to address these gaps. The framework was demonstrated using limiting-case transient conditions from a prototypic high-temperature gas-cooled reactor (HTGR). It was then applied to develop a matrix of experiments that could be performed in the Transient Reactor Test Facility (TREAT) to (1) evaluate UCO-fueled particle performance at moderate and high heat rates, (2) assess whether historical testing involving UO 2 -fueled particles is applicable to modern UCO-fueled particles, (3) deconvolute the impacts of temperature and heat rate on particle transient response, and (4) collect the data needed for fuel performance model validation and/or further development.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Seismic response of vertical dry storage casks under three-dimensional earthquake motions

Ensuring the long-term seismic safety of dry storage casks (DSCs) is becoming increasingly critical as these systems evolve from temporary to de facto permanent repositories for spent nuclear fuels. Traditional seismic soil–structure interaction (SSI) assessment methods use one-dimensional deconvolution or simplified boundary conditions to model incident waves. Although computationally appealing, simplifying assumptions may alter the seismic risk by neglecting the full complexity of three-dimensional (3D) wave propagation effects. To address this challenge, this paper introduces a novel high-fidelity computational framework that leverages the Domain Reduction Method (DRM) with perfectly matched layers (PML) to accurately transfer complex, 3D seismic wavefields from regional-scale fault-rupture simulations into local-scale finite element models of DSCs. Using broadband, physics-based ground motions from a generic M w 7.0 strike-slip event, both single-cask and multi-cask configurations were investigated under near- and far-field conditions. Emphasis is placed on capturing complex SSI, spatial variability in the ground motion, and nonlinear phenomena such as cask rocking and sliding. Numerical results demonstrate that near-field conditions, where forward directivity and fling-step effects dominate, lead to significantly higher DSC rocking and sliding. Far-field cases, by contrast, generally exhibit modest responses. Incorporating SSI tends to amplify or alter DSC response spectra and introduce response variability, which underscores the need for site-specific evaluations and robust modeling approaches to ensure the seismic integrity of DSCs in interim spent fuel storage installations.

Das, Tonmoy↗
DOE OSTI2025

Optimising the processing and storage of visibilities using lossy compression

The next-generation radio astronomy instruments are providing a massive increase in sensitivity and coverage, largely through increasing the number of stations in the array and the frequency span sampled. The two primary problems encountered when processing the resultant avalanche of data are the need for abundant storage and the constraints imposed by I/O, as I/O bandwidths drop significantly on cold storage. An example of this is the data deluge expected from the SKA Telescopes of more than 60 PB per day, all to be stored on the buffer filesystem. While compressing the data is an obvious solution, the impacts on the final data products are hard to predict. In this paper, we chose an error-controlled compressor – MGARD – and applied it to simulated SKA-Mid and real pathfinder visibility data, in noise-free and noise-dominated regimes. As the data have an implicit error level in the system temperature, using an error bound in compression provides a natural metric for compression. MGARD ensures the compression incurred errors adhere to the user-prescribed tolerance. To measure the degradation of images reconstructed using the lossy compressed data, we proposed a list of diagnostic measures, exploring the trade-off between these error bounds and the corresponding compression ratios, as well as the impact on science quality derived from the lossy compressed data products through a series of experiments. We studied the global and local impacts on the output images for continuum and spectral line examples. We found relative error bounds of as much as 10%, which provide compression ratios of about 20, have a limited impact on the continuum imaging as the increased noise is less than the image RMS, whereas a 1% error bound (compression ratio of 8) introduces an increase in noise of about an order of magnitude less than the image RMS. For extremely sensitive observations and for very precious data, we would recommend a 0.1% error bound with compression ratios of about 4. These have noise impacts two orders of magnitude less than the image RMS levels. At these levels, the limits are due to instabilities in the deconvolution methods. We compared the results to the alternative compression tool DYSCO, in both the impacts on the images and in the relative flexibility. MGARD provides better compression for similar error bounds and has a host of potentially powerful additional features.

Techniques: interferometric↗
DOE OSTI2026

Machine learning surrogates for ion energy–angle distributions in thermal and RF plasma sheaths

Ion energy–angle distributions (IEADs) at material surfaces are a critical input for plasma–material interaction (PMI) studies in fusion devices, yet they are computationally expensive to obtain using particle-in-cell (PIC) simulations. In this work, we develop a machine learning surrogate based on a deep deconvolutional neural network (DDeCNN) trained on large databases generated with the hPIC2 code. The surrogate is capable of reconstructing IEADs from sheath parameters for both thermal and radio-frequency (RF) plasmas, including cases with multiple ion species. Across thousands of test cases, the model achieves high accuracy, with over 97 % of predictions classified as good or average based on standard error metrics (MAE, MSE, L2). Even in the more challenging RF and multi-species regimes, the surrogate reliably captures the multi-peak structure of PIC results. Once trained, the surrogate produces IEADs in milliseconds on a common workstation, yielding speedups of six to seven orders of magnitude compared with running a full PIC simulation. This computational gain enables dense parameter scans and direct coupling of IEAD predictions with PMI and erosion models on whole-device scales in fusion-relevant conditions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Removal of Homogeneous Broadening from 1 H-Detected Multidimensional Solid-State NMR Spectra

1 H-detected magic-angle spinning (MAS) NMR experiments have revolutionized the NMR studies of biological and inorganic solids by providing unparalleled sensitivity and resolution. Despite these gains, homogeneous broadening, originating from the incomplete removal of homonuclear dipolar interactions under fast MAS, remains highly prevalent and limits the achievable resolution. In direct analogy to super-resolution microscopy methods, we show that resolution beyond that currently achievable by fast MAS alone can be obtained by experiment-driven deconvolution. Following the acquisition of a single 2D NMR spectrum to measure the frequency-dependent homogeneous lineshapes, any number of 1 H-detected spectra can be enhanced in resolution, yielding comparable spectra as obtained with twice the MAS frequency. In conclusion, the versatility of this approach is demonstrated in the enhancement of single- and double-quantum homonuclear correlation spectra, in addition to heteronuclear correlation spectra acquired on a surface organometallic complex and the protein GB1.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Characterization of Gas-Phase Native(-like) Proteins Using Structures for Lossless Ion Manipulations

High-resolution mobility-based ion separations in Structures for Lossless Ion Manipulations (SLIM) have been useful for ion mobility separations for a variety of molecular classes in the gas phase. Here, in this study, we present multipass SLIM separations for gas-phase proteins in their near-native state exhibiting charge-state-dependent arrival time distributions using carbonic anhydrase (29 kDa), alcohol dehydrogenase (148 kDa), and apo-transferrin (79 kDa). The experimental CCS values were obtained from calibration curves for the arrival times of Agilent Tune Mix ions. For multipass separations, the ATDs were converted to CCS values by deconvoluting the multipass arrival times into accurate single-pass values amenable to the single-pass calibration curves. Mass spectra of carbonic anhydrase (CA) showed three different charge states (z = 9+ to 11+). Their corresponding mobility peaks were baseline-separated by using 8-m single-pass separations. When compared to the corresponding drift tube ion mobility (DTIMS) measurements, the CCS values obtained from DTIMS and SLIM were in agreement within experimental error. Single-pass analysis of alcohol dehydrogenase (ADH) exhibits three predominant charge states (z = 23+ to 25+) with mobility overlap between adjacent charge states. The mobility peak resolution for ADH improved with multipass separations (up to 24-m path length). In addition, CCS distributions obtained for charge states z = 16+ to 18+ of apo-transferrin reveal a transition from a compact unimodal form (z = 18+ and 19+) to broader multimodal CCS distributions for z = 16+. For apo-transferrin, 40-m multipass separations were performed allowing for complete isolation of the selected mobility range corresponding to z = 17+, leading to selective isolation of a narrow arrival time window. The extended mobility separations provided minimal alterations to the structure of the proteins, and the experimentally derived CCS values showed minimal change as a function of the separation time or number of passes. Mobility-based ion separations for native-like proteins, using SLIM, open opportunities for native-IMS applications as well as other manipulations enabled by SLIM-like mobility-selective isolation and collection.

charge state distribution↗
DOE OSTI2024

Effect of H + Exchange and Surface Impurities on Bulk and Interfacial Electrochemistry of Garnet Solid Electrolytes

Contact loss and current constriction pose significant challenges at the Li metal interface of solid-state batteries. For garnet-structured Li 7 La 3 Zr 2 O 12 (LLZO), these effects are amplified by Li + /H + exchange and surface contamination reactions, which lead to conductivity losses and poor Li wetting. In this study, we utilize a variety of surface treatment processes across 37 cells to selectively induce proton exchange and contamination reactions in LLZO. The resulting bulk and surface chemistry is systematically characterized and correlated to changes in electrochemical properties. Additionally, we combine impedance analysis and finite element method modeling to deconvolute sources of impedance contributions at the Li metal interface. Specifically, we show that constriction impedance at the Li metal interface arises not solely from voids, but also from ionically-resistive surface contaminants. Further, these findings emphasize the connection between ionic conductivity and constriction, demonstrating that micron-scale ionically-resistive components increase constriction even with identical contact geometries. Finally, we leverage our comprehensive dataset to highlight unstable overpotential growth as a failure mechanism, additionally showing that the phase of a cell’s impedance is a sensitive indicator for the onset of interfacial instability. Overall, this study clarifies the impacts of proton exchange and surface contamination on electrochemical properties at the Li|solid electrolyte interface and elucidates insights that are generalizable to other solid-state battery systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Expanding Configurational Complexity through Dipole Dilution in Pseudohalide Argyrodite Ion Conductors

The advantageous properties of (pseudo)halide argyrodite ion conductors of the formula Li 6 PS 5 X (X = Cl – , Br – , I – , CN – ) have motivated extensive studies of their structure-transport relationships, particularly as they pertain to the role of atomic site disorder. The argyrodite structure can accommodate additional configurational complexity to promote ion transport via extended three-anion site mixing and the potential for orientational disorder of molecular anions. In this work, we explore a ternary anion system including the cyanide anion, expanding site disorder and introducing dipolar orientations as an additional degree of freedom. We prepared the series Li 6 PS 5 (CN) 1–x Br x , in which the dipolar cyanide anions are systematically diluted with bromide. We find that anion disorder, as determined by synchrotron and neutron diffraction and quantified by configurational entropy (S config ), is correlated with lowered activation barriers and increased lithium ion conductivity. We propose that S config describes the electrostatic heterogeneity of the Li environments, flattening the energetic landscape for ion transport. While anion substitution strongly impacts the activation barrier for transport, the temperature-independent Arrhenius prefactor does not follow the same trend. Through heat-capacity measurements of attempt frequency and deconvolution of terms within the prefactor, we rationalize the apparent decoupling of activation energy and prefactor to strong cyanide-lithium interactions that increase the entropy of migration. Together, these results expand the structure–property relationships in the argyrodite family to encompass multiple facets of disorder and the subsequent impact on lithium ion transport.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Optimizing Cryo-Focused Pyrolysis GC/MS for Tracing Soil Organic Matter Across Diverse Ecosystems

The cycling of organic matter in terrestrial soils and sediments is central to a range of biogeochemical processes that regulate nutrient cycling, crop productivity, trace gas emissions, and contaminant transport. Pyrolysis-gas chromatography/mass spectrometry (py-GC/MS) is a powerful tool for characterizing bulk soil organic matter (SOM) at the molecular level. In this study, we used a cryo-focused py-GC/MS system to analyze soil samples from seven diverse ecosystems: vernal pool, prairie pothole, temperate forest, tropical forest, tundra, wildfire-affected boreal forest, and grassland. We addressed a key bottleneck in molecular-level SOM characterization by developing an automated data analysis pipeline to optimize py-GC/MS and complementary evolved gas analysis/mass spectrometry (EGA/MS) methods, incorporating advanced tools for peak deconvolution, developing a custom compound class library, and implementing fragmentation spectrum-based molecular networking for the first time. This improved workflow was applied to soil samples from all seven ecosystems, including multiple depths and density fractions. Our findings demonstrate that ecosystem type plays a dominant role in shaping compositional differences in SOM. We also identified trends in the source of SOM compounds (e.g., microbial vs plantderived) across soil depth and density fractions, which are critical for understanding persistence and turnover of SOM. Our molecular networking analysis indicated that although many compounds are widespread across ecosystems, others are restricted to specific environments, such as wetlands. This underscores the utility of molecular-level data in elucidating the complexity of SOM composition and the environmental drivers that shape it. Such molecular-level insights can deepen our knowledge of biogeochemical SOM cycles.

54 ENVIRONMENTAL SCIENCES↗